Psychiatry

Deconstructing depression by machine learning: the POKAL-PSY study.

Unipolar depression is a prevalent and disabling condition, often left untreated. In the outpatient setting, general practitioners fail to recognize depression in about 50% of cases mainly due to somatic comorbidities. Given the significant economic, social, and interpersonal impact of depression and its increasing prevalence, there is a need to improve its diagnosis and treatment in outpatient ca...

Select or adjust? How information from early treatment stages boosts the prediction of non-response in internet-based depression treatment.

BACKGROUND: Internet-based interventions produce comparable effectiveness rates as face-to-face therapy in treating depression. Still, more than half of patients do not respond to treatment. Machine learning (ML) methods could help to overcome these low response rates by predicting therapy outcomes on an individual level and tailoring treatment accordingly. Few studies implemented ML algorithms in...

Using Conversational AI to Facilitate Mental Health Assessments and Improve Clinical Efficiency Within Psychotherapy Services: Real-World Observational Study.

BACKGROUND: Most mental health care providers face the challenge of increased demand for psychotherapy in the absence of increased funding or staffing...

A feasibility study of robot-assisted percutaneous reduction and fixation technique for treating posterolateral depression tibial plateau fractures.

Posterolateral (PL)-depression fractures of the tibial plateau are difficult to manage. The aim of this study was: (1) to present our experience with ...

The preliminary efficacy of virtual agent-assisted intelligent rehabilitation treatment (Echo app v2.0) in patients with alcohol use disorders: Study protocol for a randomized controlled trial.

BACKGROUND: Alcohol use disorder (AUD) is one of the most common substance use disorders. People with AUD are in great need of highly accessible and c...

Development of depression assessment tools using humanoid robots -Can tele-operated robots talk with depressive persons like humans?

BACKGROUND: Depression is a common mental disorder and causes significant social loss. Early intervention for depression is important. Nonetheless, de...

Robotic pancreatic tumor enucleation by the double bipolar technique using the da Vinci SP system: An initial case report with a technical detail.

Pancreatic tumor enucleation is a procedure that can preserve pancreatic function and is sometimes performed using a minimally invasive approach. Rece...

Unlocking the potential: Exploring the opportunities for occupational therapists in cyberpsychology.

It has long been established that occupational therapists (OTs) play an important role in assisting clients suffering from a variety of physical and m...

Selectively predicting the onset of ADHD, oppositional defiant disorder, and conduct disorder in early adolescence with high accuracy.

INTRODUCTION: The externalizing disorders of attention deficit hyperactivity disorder (ADHD), oppositional defiant disorder (ODD), and conduct disorde...

Depression Identification Using EEG Signals via a Hybrid of LSTM and Spiking Neural Networks.

Depression severity can be classified into distinct phases based on the Beck depression inventory (BDI) test scores, a subjective questionnaire. Howev...

Toward explainable AI (XAI) for mental health detection based on language behavior.

Advances in artificial intelligence (AI) in general and Natural Language Processing (NLP) in particular are paving the new way forward for the automat...

Bimodal Feature Analysis with Deep Learning for Autism Spectrum Disorder Detection.

Autism Spectrum Disorder (ASD) is a complex and heterogeneous neurodevelopmental disorder which affects a significant proportion of the population, wi...

Systematic bibliometric and visualized analysis of research hotspots and trends in artificial intelligence in autism spectrum disorder.

BACKGROUND: Artificial intelligence (AI) has been the subject of studies in autism spectrum disorder (ASD) and may affect its identification, diagnosi...

Predicting Outcomes of Antidepressant Treatment in Community Practice Settings.

OBJECTIVE: The authors examined whether machine-learning models could be used to analyze data from electronic health records (EHRs) to predict patient...

Deep Learning and Geriatric Mental Health.

The goal of this overview is to help clinicians develop basic proficiency with the terminology of deep learning and understand its fundamentals and ea...

On artificial intelligence and global mental health.

Artificial intelligence (AI) is affecting global societies and reshaping the status quo. AI technologies possess great potential to tackle some of man...

Stress Monitoring in Free-Living Environments.

Stress monitoring is an important area of research with significant implications for individuals' physical and mental health. We present a data-driven...

Evaluation of deep learning-based depression detection using medical claims data.

Human accuracy in diagnosing psychiatric disorders is still low. Even though digitizing health care leads to more and more data, the successful adopti...

Arts therapies for mental disorders in COVID-19 patients: a comprehensive review.

BACKGROUND AND OBJECTIVE: The COVID-19 global pandemic has necessitated the urgency for innovative mental health interventions. We performed a compreh...

Clinical decision-making in benzodiazepine deprescribing by healthcare providers vs. AI-assisted approach.

AIMS: The aim of this study was to compare the clinical decision-making for benzodiazepine deprescribing between a healthcare provider (HCP) and an ar...